Archive for the ‘Web Text Simplification’ Category

AI and Disability Interview

2019/06/17

AXS Chat recently posted to YouTube an interview of me about my artificial intelligence (AI) research and work for people with disabilities. I talk, in part, about:

  • the promise of a text-comprehension parallel between AI and people with intellectual disabilities;
  • how AI-driven Web text simplification will benefit other populations, such as non-native language speakers; and
  • my work to make sure people with intellectual disabilities and/or autism are not left out of online education.

I thank the AXS Chat members, Neil Milliken, Debra Ruh, and Antonio Santos, for their tireless work to inform the world about inclusion and technology.

Amazon re:MARS Accessibility

2019/06/14


Amazon Machine Learning Research Awards generously sponsored my colleagues and me to participate in last week’s Amazon re:MARS Conference. It was a global artificial intelligence (AI) event focused on Machine Learning, Automation, Robotics, and Space.

The conference was great with accessibility. I was assigned an employee who guided me everywhere and was just wonderful. The conference website was accessible and easy to navigate. When I identified accessibility problems with the mobile app and with SageMaker tools, Amazon personnel immediately assured me they would be fixed.

The sponsorship included participation in the re:MARS VIP Leadership Networking Reception. I was honored to speak with members of Amazon leadership as well as senior researchers from industry and academia.

We discussed:

  • my AI-driven, Web text simplification research;
  • AI fairness for people with disabilities; and
  • developing an Alexa skill for DisabilityInfo.org.

 

AI Web Text Simplification: CSUN 2019

2019/03/04

I will soon present part of my AI-Driven Web Text SiCSUN Center on Disabilitiesmplification research.

My talk:

We tested if people with intellectual disabilities understand Web text simplified with plain-language standards. (Spoiler: They do!)

We are operationalizing plain-language standards essentially to develop:

  • a reliable, easy-to-use method for human editors to create simple text; and
  • algorithms for AI to recognize and to create simple text.

 

 

 

 

AI Web Text Simplification: Partners

2019/01/21

For my AI-Driven Web Text Simplification research, I lead a coalition of corporate and academic partners. They include:

AI-Driven Web Text Simplification: Intro

2019/01/07

Research Goal

Make Web text so simple people understand it the first time they read it.

Background

Text comprises the vast majority of Web content. Poor reading comprehension presents significant challenges to many populations, including people with cognitive disabilities, non‐native speakers, and people with low literacy.

Text simplification aims to reduce text complexity while retaining its meaning. Manual text simplification research has been ongoing for decades. Yet no significant effort has been made to automate text simplification except as a preprocessor for natural-language processing tasks such as machine translation and summarization.

Short-Term Approach

In the short term, my partners and I are improving manual text simplification by creating effective, replicable methods for humans to produce it. We use national and international plain language standards. We conduct pilot studies to see if people comprehend our human-curated, simplified Web text better than typical Web text.

Long-Term Approach

In the long term, my partners and I are developing artificial intelligence (AI) capabilities to produce simple Web text on a mass scale. We are training AI with enormous sets of aligned sentence pairs (typical/simple). We will soon start crowd-sourcing the generation of training data.

I will provide details in future blog posts.


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